fix: use Spark type names in ANSI abs overflow errors

[Smallfu666]

Which issue does this PR close?

Closes #5356.

Rationale for this change

Under ANSI mode, abs on an integer minimum raises ARITHMETIC_OVERFLOW. Comet's
Spark error shim turns the native fromType field into Spark's arithmetic-overflow
message by passing fromType + " overflow" to
QueryExecutionErrors.arithmeticOverflowError. native/spark-expr/src/math_funcs/abs.rs
was passing Arrow-style type names as fromType, hard-coded at each arm, so Comet
reported Int64 overflow where Spark reports long overflow, and Int32 overflow
where Spark reports integer overflow.

SET spark.sql.ansi.enabled=true;
SELECT abs(v) FROM t;   -- v BIGINT, single row -9223372036854775808

Spark: [ARITHMETIC_OVERFLOW] long overflow.
Comet before this PR: same error class, Int64 overflow.

The message determines the user-visible Spark exception message.

What changes are included in this PR?

The eight from_type strings in abs.rs, four on the array path through ansi_compute_op! and
four on the scalar path, now carry Spark's name instead of Arrow's:

Arrow	was	now
Int8	"Int8"	"byte"
Int16	"Int16"	"short"
Int32	"Int32"	"integer"
Int64	"Int64"	"long"

The mapping is not uniform across the supported Spark versions. Spark's Abs negates
through MathUtils.negateExact. For int and long that surfaces the JDK
ArithmeticException text, which is integer overflow and long overflow on 3.4, 3.5
and 4.x alike. Byte and short match 4.x only: 3.4 and 3.5 route those two widths to
QueryExecutionErrors.unaryMinusCauseOverflowError, raising
_LEGACY_ERROR_TEMP_2043 (- <sqlValue> caused overflow.), a different error class,
so no single string can satisfy every version. 4.0 sends all four widths through
MathUtils.negateExact. I originally reproduced this against 3.4.3, 3.5.8, 4.0.2 and
4.1.2 jars; the same code paths remain in the currently supported 3.5.9 and 4.1.3
sources.

Decimal128 and Decimal256 are deliberately left alone. Those guards fire only at i128::MIN and
i256::MIN, which no Spark decimal reaches at its maximum precision of 38, and decimal overflow
goes through a different Spark error class. That belongs in its own change.

How are these changes tested?

abs_ansi.sql. The fixture already ran abs(v) over a column of each width at its minimum, but
every assertion was expect_error(overflow), which "Int64 overflow" satisfies exactly as happily
as "long overflow". It could not fail on this bug. The int and long cases now assert the full
message, expect_error(integer overflow) and expect_error(long overflow).

Byte and short stay on the loose pattern, and the fixture says why in a comment: ExpectError
asserts the pattern against Spark's message as well as Comet's, and on 3.4 and 3.5 Spark genuinely
words those two differently.

ExpectError runs Spark and Comet separately and requires both errors to contain the
pattern. It does not by itself prove native coverage. Native reachability for the INT
column case is established by the negative control below: reverting only the production
change while keeping the strengthened fixture makes the Comet run fail on
integer overflow, while Spark is unchanged.

Negative control at the Spark level, production reverted and the fixture kept:
org.apache.comet.CometSqlFileTestSuite on Spark 3.5 / Scala 2.12 goes from 444 run, 444
succeeded to 444 run, 443 succeeded, 1 failed, the failure being
expressions/math/abs_ansi.sql:57, SELECT abs(v) FROM ansi_test_abs_int, does not contain 'integer overflow'. Spark is identical between the two runs, so that failure is the Comet side of
the assertion.

Rust. The ANSI branches had no error assertions at all, so this adds two tests:

• test_ansi_abs_min_uses_spark_type_names downcasts to SparkError::ArithmeticOverflow and
  asserts from_type for all four widths on both the array and the scalar path. Asserting the
  variant and the field rather than a substring of the rendered string.
• test_ansi_abs_just_inside_boundary_succeeds checks MIN + 1 for each width still returns MAX,
  so the guard is not over-broad.

Negative control on the unpatched production code with these tests kept: 18 passed, 1 failed,
the failure being assertion left == right failed, left: "Int8", right: "byte". Note it stops at
the first case in the table, so what is proven red on main is the byte case in Rust and the int
case at the Spark level.

Also run on this branch: the full datafusion-comet-spark-expr lib suite, cargo fmt --all -- --check, and cargo clippy -p datafusion-comet-spark-expr --all-targets -- -D warnings.

Note for reviewers

TINYINT and SMALLINT have no Spark-level regression test here, only the Rust one, for the version
reason above. If you would rather see them covered, the fixture would need to gate the assertion on
the Spark version, which felt like more machinery than the case is worth.

[sunchao]

Reviewed the ANSI abs overflow type names against the canonical Spark 3.5 and 4.0 error paths. I found no P1/P2 issues introduced by this change. A Spark 4.0.4 baseline confirmed the byte, short, integer, and long overflow names.

CI has now started. The rust-test job fails during Clippy 1.98 on chunks_exact_to_as_chunks in spark_bit_array.rs and manual_isolate_lowest_one in mersenne.rs, before tests run. I verified both files are unchanged from this PR's merge base. The full CI matrix has not passed. I did not run the full Comet abs test suite locally.

[Smallfu666]

Thanks for the review, and for checking those two files against the merge base.

That clippy failure came from #5400 , which landed after this branch was cut, so I rebased onto current main to pick it up. Workspace clippy is clean locally now.